karoldobiczek/fomc-communication

该数据集是从FOMC（联邦公开市场委员会）的演讲、会议记录和新闻稿中收集的句子集合。部分数据被手动标注为鹰派、鸽派或中立。标签映射为：LABEL 2表示中立，LABEL 1表示鹰派，LABEL 0表示鸽派。

原始信息汇总

数据集概述

基本信息

• 许可证: CC-BY-NC-4.0
• 任务类别: 文本分类
• 语言: 英语
• 标签: 金融, 反事实
• 数据集大小: 1K<n<10K

数据来源

• 数据集改编自Shah等人的原始工作，详见原始数据集链接。

数据描述

• 数据集包含来自FOMC演讲、会议纪要和新闻发布会的句子。部分数据已手动标注为鹰派、鸽派或中性。

标签映射

• LABEL 2: 中性
• LABEL 1: 鹰派
• LABEL 0: 鸽派

引用信息

• 如需使用此数据集，请引用以下论文： c @inproceedings{shah-etal-2023-trillion, title = "Trillion Dollar Words: A New Financial Dataset, Task {&} Market Analysis", author = "Shah, Agam and Paturi, Suvan and Chava, Sudheer", booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", month = jul, year = "2023", address = "Toronto, Canada", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.acl-long.368", doi = "10.18653/v1/2023.acl-long.368", pages = "6664--6679", abstract = "Monetary policy pronouncements by Federal Open Market Committee (FOMC) are a major driver of financial market returns. We construct the largest tokenized and annotated dataset of FOMC speeches, meeting minutes, and press conference transcripts in order to understand how monetary policy influences financial markets. In this study, we develop a novel task of hawkish-dovish classification and benchmark various pre-trained language models on the proposed dataset. Using the best-performing model (RoBERTa-large), we construct a measure of monetary policy stance for the FOMC document release days. To evaluate the constructed measure, we study its impact on the treasury market, stock market, and macroeconomic indicators. Our dataset, models, and code are publicly available on Huggingface and GitHub under CC BY-NC 4.0 license.", }